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Removed classification proto to use the existing category dataclass instead and removed NormalizedLandmarkList and LandmarkList dataclasses

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kinaryml
2022-10-30 08:23:14 -07:00
parent 0f7c5d5e90
commit f62cfd1690
9 changed files with 127 additions and 303 deletions
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mediapipe/tasks/python/test/vision/gesture_recognizer_test.py
+23 -26
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@@ -24,7 +24,7 @@ from absl.testing import parameterized
from mediapipe.python._framework_bindings import image as image_module
from mediapipe.tasks.cc.components.containers.proto import landmarks_detection_result_pb2
from mediapipe.tasks.python.components.containers import rect as rect_module
from mediapipe.tasks.python.components.containers import classification as classification_module
from mediapipe.tasks.python.components.containers import category as category_module
from mediapipe.tasks.python.components.containers import landmark as landmark_module
from mediapipe.tasks.python.components.containers import landmark_detection_result as landmark_detection_result_module
from mediapipe.tasks.python.core import base_options as base_options_module
@@ -36,12 +36,9 @@ from mediapipe.tasks.python.vision.core import image_processing_options as image
_LandmarksDetectionResultProto = landmarks_detection_result_pb2.LandmarksDetectionResult
_BaseOptions = base_options_module.BaseOptions
_Rect = rect_module.Rect
_Classification = classification_module.Classification
_ClassificationList = classification_module.ClassificationList
_Category = category_module.Category
_Landmark = landmark_module.Landmark
_LandmarkList = landmark_module.LandmarkList
_NormalizedLandmark = landmark_module.NormalizedLandmark
_NormalizedLandmarkList = landmark_module.NormalizedLandmarkList
_LandmarksDetectionResult = landmark_detection_result_module.LandmarksDetectionResult
_Image = image_module.Image
_GestureRecognizer = gesture_recognizer.GestureRecognizer
@@ -76,14 +73,11 @@ def _get_expected_gesture_recognition_result(
text_format.Parse(f.read(), landmarks_detection_result_proto)
landmarks_detection_result = _LandmarksDetectionResult.create_from_pb2(
landmarks_detection_result_proto)
gesture = _ClassificationList(
classifications=[
_Classification(label=gesture_label, index=gesture_index,
display_name='')
])
gesture = _Category(category_name=gesture_label, index=gesture_index,
display_name='')
return _GestureRecognitionResult(
gestures=[gesture],
handedness=[landmarks_detection_result.classifications],
gestures=[[gesture]],
handedness=[landmarks_detection_result.categories],
hand_landmarks=[landmarks_detection_result.landmarks],
hand_world_landmarks=[landmarks_detection_result.world_landmarks])
@@ -115,25 +109,27 @@ class GestureRecognizerTest(parameterized.TestCase):
self.assertLen(actual_result.handedness, len(expected_result.handedness))
self.assertLen(actual_result.gestures, len(expected_result.gestures))
# Actual landmarks match expected landmarks.
self.assertLen(actual_result.hand_landmarks[0].landmarks,
len(expected_result.hand_landmarks[0].landmarks))
actual_landmarks = actual_result.hand_landmarks[0].landmarks
expected_landmarks = expected_result.hand_landmarks[0].landmarks
self.assertLen(actual_result.hand_landmarks[0],
len(expected_result.hand_landmarks[0]))
actual_landmarks = actual_result.hand_landmarks[0]
expected_landmarks = expected_result.hand_landmarks[0]
for i in range(len(actual_landmarks)):
self.assertAlmostEqual(actual_landmarks[i].x, expected_landmarks[i].x,
delta=_LANDMARKS_ERROR_TOLERANCE)
self.assertAlmostEqual(actual_landmarks[i].y, expected_landmarks[i].y,
delta=_LANDMARKS_ERROR_TOLERANCE)
# Actual handedness matches expected handedness.
actual_top_handedness = actual_result.handedness[0].classifications[0]
expected_top_handedness = expected_result.handedness[0].classifications[0]
actual_top_handedness = actual_result.handedness[0][0]
expected_top_handedness = expected_result.handedness[0][0]
self.assertEqual(actual_top_handedness.index, expected_top_handedness.index)
self.assertEqual(actual_top_handedness.label, expected_top_handedness.label)
self.assertEqual(actual_top_handedness.category_name,
expected_top_handedness.category_name)
# Actual gesture with top score matches expected gesture.
actual_top_gesture = actual_result.gestures[0].classifications[0]
expected_top_gesture = expected_result.gestures[0].classifications[0]
actual_top_gesture = actual_result.gestures[0][0]
expected_top_gesture = expected_result.gestures[0][0]
self.assertEqual(actual_top_gesture.index, expected_top_gesture.index)
self.assertEqual(actual_top_gesture.label, expected_top_gesture.label)
self.assertEqual(actual_top_gesture.category_name,
expected_top_gesture.category_name)
def test_create_from_file_succeeds_with_valid_model_path(self):
# Creates with default option and valid model file successfully.
@@ -235,12 +231,13 @@ class GestureRecognizerTest(parameterized.TestCase):
expected_result = _get_expected_gesture_recognition_result(
_THUMB_UP_LANDMARKS, _THUMB_UP_LABEL, _THUMB_UP_INDEX)
# Only contains one top scoring gesture.
self.assertLen(recognition_result.gestures[0].classifications, 1)
self.assertLen(recognition_result.gestures[0], 1)
# Actual gesture with top score matches expected gesture.
actual_top_gesture = recognition_result.gestures[0].classifications[0]
expected_top_gesture = expected_result.gestures[0].classifications[0]
actual_top_gesture = recognition_result.gestures[0][0]
expected_top_gesture = expected_result.gestures[0][0]
self.assertEqual(actual_top_gesture.index, expected_top_gesture.index)
self.assertEqual(actual_top_gesture.label, expected_top_gesture.label)
self.assertEqual(actual_top_gesture.category_name,
expected_top_gesture.category_name)
def test_recognize_succeeds_with_num_hands(self):
# Creates gesture recognizer.